Click the above “Mechanical and Electronic Engineering Technology” to follow us The MNIST (Modified National Institute of Standards and Technology) dataset is a classic dataset for handwritten digit recognition, widely used in the fields of machine learning and deep learning. It was created by the National Institute of Standards and Technology (NIST) in the United … Read more
In previous articles, we have introduced two types of image segmentation loss functions. Today, we will share commonly used multi-class image segmentation loss functions such as multi-class cross-entropy, weighted multi-class cross-entropy, multi-class Dice coefficient, multi-class Focal Loss, etc., and provide code to reproduce the above loss functions in TensorFlow. 1. Cross Entropy The cross-entropy loss … Read more
The global deep learning systems market is expected to reach $93.34 billion by 2028, with a compound annual growth rate of 39.1%. Deep learning, also known as deep neural learning, is a subset of machine learning and an application of artificial intelligence, where machines mimic the working of the human brain and use artificial neural … Read more
Commonly used image segmentation loss functions include binary cross-entropy, dice coefficient, Tversky, and Focal Loss. Today, I will reproduce the above loss functions in TensorFlow and compare the results. 1. Cross Entropy The cross-entropy loss function compares the predicted class values with the target values on a pixel-by-pixel basis, and then averages the values over … Read more
Deep Learning Frameworks Author: Horace He Revise: louwill source: https://thegradient.pub/state-of-ml-frameworks-2019-pytorch-dominates-research-tensorflow-dominates-industry/ For many practitioners in the deep learning industry, mastering one or more deep learning frameworks is one of the essential skills for daily work. After a period of chaos in the deep learning framework market, a dominant market structure has gradually formed with TensorFlow and … Read more
Follow the public account “ML_NLP” Set as “Starred”, heavy content will be delivered first! Source | Machine Heart “The official documentation is messy, the search function is difficult to use, and the API is hideous…” This is the complaint of many people about the TensorFlow official documentation. But complaints aside, in the industry, you cannot … Read more
From ｜jacobbuckman.com Author｜Jacob Buckman Compiled by｜Machine Heart (No Reposting), Xiaoshi Although for most people the development language of TensorFlow is Python, it is not a standard Python library. This neural network framework runs by constructing a “computation graph,” which can be quite confusing for many beginners trying to understand its logic. In this article, Jacob … Read more
This article contains 7196 words, and it is recommended to read in 10 minutes This article explains how to use TensorFlow for machine learning and deep learning. 1. Introduction The success of deep learning algorithms has led to groundbreaking advances in artificial intelligence research and applications, greatly changing our lives. More and more developers are … Read more
Click the “Beginner’s Guide to Vision” above, and choose to add “Star” or “Top“ Heavy content delivered promptly Why Use Multi-GPU Parallel Training In simple terms, there are two reasons: the first is that the model cannot fit on a single GPU, but can run completely on two or more GPUs (like the early AlexNet). … Read more
Original Title: An Introduction to PyTorch – A Simple yet Powerful Deep Learning Library Author: FAIZAN SHAIKH Translator: He Zhonghua This article is about 3600 words, recommended reading time is 15 minutes.This article will guide you step by step through PyTorch with practical examples. Introduction Every once in a while, a Python library emerges that … Read more